The invention disclosed herein relates generally to image recognition methods and systems, and more specifically to a simple low cost edge extraction operator to convert gray scale information into binary edge information necessary to allow measurement and data acquisition.
Machine vision systems are becoming increasingly in demand for a wide variety of tasks, of which examples include object recognition, parts inspection, automatic production and assembly by robots, surveillance of scene to determine any changes with time, and many other applications. A straight forward approach to handling these tasks involves subdividing a scene into pixels, the number of which depends on the required resolution. Each pixel is then examined to determine the gray scale of light received therefrom, and perhaps other variables. The information from each pixel may then be compared with that of surrounding pixels or of the same pixel from a preceding frame, and then combined with information derived from other pixels and/or otherwise processed to provide object detection, recognition, inspection, etc. Such an approach generally results in processing much unuseful information which results in wasted time and places unnecessary demands on the processing system. The reason that this approach is inefficient is that a majority of a scene is frequently relatively uniform background around a single object of interest. In addition, much of the view of an object within its edges may be uniform and not useful for detection, recognition and inspection purposes. Thus, in many instances only the location of the edges of an object is necessary for performance of a required task. Ignoring information as to the uniform background and uniform interior surface of an object generally results in substantial decreases in imaging processing time and demands placed on the processing system.
The applicant has devised a unique, simple and low cost approach to detecting and representing the edges of an object which avoids the disadvantages of more elaborate conventional approaches, and yet meets the requirements of a large variety of situations.